Technical Report CIS-2005-05

Gabor features are a common choice for texture analysis. There are several popular sets of Gabor filters. These sets are usually designed based on representation considerations.
We propose here an alternative criterion for designing the filters
set. We consider a set of filters and their responses to a pairs
of harmonic signals. Two signals are considered separable if the
corresponding two sets of responses are disjoint in at
least one of the responses. We look for the set of Gabor filters
maximizing the fraction of separable harmonic signals. The
proposed semi-analytical algorithm calculates filters parameters
for the optimal set, given the desired number of filters and the
frequency range of possible signals. The resulting filters are
significantly different from those traditionally used.
We tested the proposed filters both in texture segmentation
and texture recognition aspects with commonly used discrimination
algorithms for each of the tasks. We show that, as expected, the
resulting filters perform better than the traditional ones in
discriminating synthetic and real textures. An important
side effect of using the proposed filters with the popular
features distribution based methods, considering a feature vector
composed of the filters' responses, is the possibility to use a
more compact (a lower number of feature vector prototypes)
representation of the texture classes than using the common
filters.

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